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Record W3113646405 · doi:10.1139/cgj-2019-0366

Flow liquefaction potential of loose sand: stress path envelope and energy-based evaluation

2020· article· en· W3113646405 on OpenAlexvenueno aff
Kun Pan, Zhongxuan Yang, Yuanqiang Cai

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsLiquefactionGeotechnical engineeringSoil liquefactionStress pathTriaxial shear testFlow (mathematics)GeologyPore water pressureStiffnessShear stressEffective stressShear (geology)Materials scienceMechanicsComposite materialPetrology

Abstract

fetched live from OpenAlex

Flow liquefaction, which is characterized by sudden collapse following the unstable behavior of saturated loose sand, may lead to the most catastrophic consequence of all liquefaction-related phenomena. This note presents a systematic experimental investigation into the flow liquefaction potential of sand under various initial and cyclic shear conditions. The cyclic flow liquefaction responses are compared with the monotonic shear results under an identical initial testing condition. It is found that the effective stress path of a monotonic test appears to envelop that of its corresponding cyclic test. The energy-based liquefaction potential evaluation indicates that the accumulative dissipated energy is uniquely correlated not only with the pore pressure and axial strain induced in sand, but also with the degraded stiffness during cyclic loading. Furthermore, the energy capacity for triggering the flow liquefaction appears to be intimately related to the cyclic resistance of sand; this signifies the potential applicability of energy-based liquefaction potential evaluation using strength data available in conventional analysis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.195
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2020
Admission routes1
Has abstractyes

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